Search results for: Jon Weissman
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IEEE Transactions on Parallel and Distributed Systems > 2017 > 28 > 11 > 3229 - 3242
Centralized cloud infrastructures have become the popular platforms for data-intensive computing today. However, they suffer from inefficient data mobility due to the centralization of cloud resources, and hence, are highly unsuited for geo-distributed data-intensive applications where the data may be spread at multiple geographical locations. In this paper, we present Nebula: a dispersed edge cloud...
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2017 Resilience Week (RWS) > 127 - 132
Centralized cloud platforms have been widely utilized for data-intensive computing in many domains. However, such systems are not suitable for geo-distributed applications since they require data to be moved to a central location for processing. Recent works have proposed an alternative cloud platform, called edge cloud that provides computational and/or storage resources at the edge, enabling in-situ...
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The Internet of Things (IoT) is enabling a multitude of new applications. Current systems exhibit inefficiencies which stem from applications being isolated and opportunities for sharing and contention resolution ignored. We propose a new system called Constellation that enables synergies between applications which we believe can make IoT systems more efficient. We explore such synergies and provide...
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IEEE Transactions on Cloud Computing > 2016 > 4 > 3 > 293 - 306
MapReduce has proven remarkably effective for a wide variety of data-intensive applications, but it was designed to run on large single-site homogeneous clusters. Researchers have begun to explore the extent to which the original MapReduce assumptions can be relaxed, including skewed workloads, iterative applications, and heterogeneous computing environments. This paper continues this exploration...
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One of the factors that limits the scale, performance, and sophistication of distributed applications is the difficulty of concurrently executing them on multiple distributed computing resources. In part, this is due to a poor understanding of the general properties and performance of the coupling between applications and dynamic resources. This paper addresses this issue by integrating abstractions...
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Lecture Notes in Computer Science > Euro-Par 2009 Parallel Processing > Topic 6: Grid, Cluster, and Cloud Computing > 389-389
Grid, Cluster, and Cloud Computing represent important points on the parallel and distributed computing platform landscape. Grids and clusters continue to generate interesting and important research. The inclusion of Cloud computing is new for 2009 and we are happy to report that our track has two high quality papers on Clouds. This year the track was very competitive and 7 out of 27 papers were selected,...
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Lecture Notes in Computer Science > Developing an Infrastructure for Mobile and Wireless Systems > Accepted Papers > 90-105
With the explosive expansion of the Internet as the global information infrastructure, coupled with rapid advances in wireless technologies, a new vision for computing is emerging. A seamless, anywhere, anytime, untethered, pervasive computing paradigm is touted as the next major paradigm shift in the way we compute and communicate. In order to realize this vision, the complexity of this environment...
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Today, many organizations need to operate on datathat is distributed around the globe. This is inevitable due to thenature of data that is generated in different locations such as videofeeds from distributed cameras, log files from distributed servers, and many others. Although centralized cloud platforms havebeen widely used for data-intensive applications, such systemsare not suitable for processing...
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The abundance of compute and storage resources available in the cloud makes it well-suited to addressing the limitations of mobile devices. We explore the use of cloud infrastructure to optimize content-centric mobile applications, which can have high communication and storage requirements, based on the analysis of user activity. We present two specific optimizations, precaching and prefetching, as...
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In this paper, we present our vision for cloud-based mobile computing using user profile information. Such information enables a series of data-driven optimizations: filtering, aggregation, and speculation, that go beyond the well-researched benefit of mobile outsourcing. These optimizations can improve performance, reliability, and energy usage. A novel aspect of our approach is to exploit the unique...
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Today, centralized data-centers or clouds have become the de-facto platform for data-intensive computing in the commercial, and increasingly, scientific domains. This is because clouds such as Amazon AWS and Microsoft Azure offer large amounts of monetized co-located computation and storage well suited to typical processing tasks such as batch analytics. However, many Big Data applications rely on...
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In this paper, we present our vision for data-driven cloud-based mobile computing. We identify the concept of Region of interest (RoI) that reflects the profile of the user in how they access information or interact with applications. Such information enables a series of data-driven optimizations: filtering, aggregation, and speculation, that go beyond the well-researched benefit of mobile outsourcing...
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Centralized cloud infrastructures have become the de-facto platform for data-intensive computing today. However, they suffer from inefficient data mobility due to the centralization of cloud resources, and hence, are highly unsuited for dispersed-data-intensive applications, where the data may be spread at multiple geographical locations. In this paper, we present Nebula: a dispersed cloud infrastructure...
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Concurrency and Computation: Practice and Experience > 25 > 11 > 1559 - 1585
It is generally accepted that the ability to develop large‐scale distributed applications has lagged seriously behind other developments in cyberinfrastructure. In this paper, we provide insight into how such applications have been developed and an understanding of why developing applications for distributed infrastructure is hard. Our approach is unique in the sense that it is centered around half...
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Distributed data-intensive workflow applications are increasingly relying on and integrating remote resources including community data sources, services, and computational platforms. Increasingly, these are made available as data, SAAS, and IAAS clouds. The execution of distributed data-intensive workflow applications can exposé network bottlenecks between clouds that compromise performance. In this...
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Map Reduce has been designed to accommodate large-scale data-intensive workloads running on large single-site homogeneous clusters. Researchers have begun to explore the extent to which the original Map Reduce assumptions can be relaxed including skewed workloads, iterative applications, and heterogeneous computing environments. Our work continues this exploration by applying Map Reduce across widely...
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IEEE Internet Computing > 2013 > 17 > 5 > 70 - 73
Cloud computing services are traditionally deployed on centralized computing infrastructures confined to a few data centers, while cloud applications run in a single data center. However, the cloud's centralized nature can be limiting in terms of performance and cost for applications where users, data, and computation are distributed. The authors present an overview of distributed clouds that might...
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Mobile devices, such as smart phones and tablets, are becoming the universal interface to online services and applications. However, such devices have limited computational power and battery life, which limits their ability to execute resource-intensive applications. Computation outsourcing to external resources has been proposed as a technique to alleviate this problem. Most existing work on mobile...
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By exploiting idle time on volunteer machines, desktop grids provide a way to execute large sets of tasks with negligible maintenance and low cost. Although desktop grids are attractive for their scalability and low cost, relying on external resources may compromise the correctness of application execution due to the well-known unreliability of nodes. In this paper, we consider a very challenging...
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By exploiting idle time on volunteer machines, desktop grids provide a way to execute large sets of tasks with negligible maintenance and low cost. Although desktop grids are attractive for cost-conscious projects, relying on external resources may compromise the correctness of application execution due to the well-known unreliability of nodes. In this paper, we consider the most challenging threat...
